The field of conversational AI is rapidly advancing, with a focus on improving healthcare and education outcomes. Recent developments have seen the integration of large language models (LLMs) with virtual agents, chatbots, and virtual reality platforms to create more effective and personalized interactions. These innovations have the potential to enhance patient care, education, and health outcomes, while also improving the overall user experience. Notably, researchers are exploring the use of role-play, context-seeking, and emotional intelligence to create more nuanced and empathetic conversational systems. The incorporation of non-verbal cues, such as facial expressions and emotional signals, is also being investigated to improve the accuracy and effectiveness of these systems. Overall, the field is moving towards more sophisticated and human-centered conversational AI solutions. Noteworthy papers include: HealthDial, which introduces a no-code LLM-assisted dialogue authoring tool for healthcare virtual agents. SARHAchat, which presents an LLM-based chatbot for sexual and reproductive health counseling. Attention to Non-Adopters, which highlights the importance of incorporating non-adopter perspectives in LLM development and evaluation.